Although extensive research in planning has been carried out for normal scenarios, path planning in emergencies has not been thoroughly explored, especially when vehicles move at a higher speed and have less space for avoiding a collision. For emergency collision avoidance, the controller should have the ability to deal with complicated environments and take collision mitigation into consideration since the problem may have no feasible solution. We propose a safety controller by using model predictive control and artificial potential function. A new artificial potential function inspired by line charge is proposed as the cost function for our model predictive controller. The new artificial potential function takes the shape of all objects into consideration. In particular, the artificial potential function that we proposed has the flexibility to fit the shape of the road structures such as the intersection, while the artificial potential function in most of the previous work could only be used in a highway scenario. Moreover, we could realize collision mitigation for a specific part of the vehicle by increasing the quantity of the charge at the corresponding place. We have tested our methods in 192 cases from 8 different scenarios in simulation. The simulation results show that the success rate of the proposed safety controller is 20% higher than using HJ-reachability with system decomposition. It could also decrease 43% of collision that happens at the pre-assigned part.
翻译:尽管对正常情况进行了广泛的规划研究,但紧急情况下的道路规划尚未进行彻底探讨,特别是当车辆以更高速度移动,避免碰撞的空间较少时,避免紧急碰撞时,控制器应有能力处理复杂的环境,并顾及减少碰撞的问题,因为问题可能没有可行的解决办法。我们建议使用模型预测控制和人工潜在功能来提供安全控制器。根据线电效应作为模型预测控制器的成本功能,提出了一个新的人工潜在功能。新的人造潜在功能将所有物体的形状考虑在内。特别是,我们提议的人为潜在功能具有灵活性,可以适应路体结构的形状,例如交叉点,而以前大多数工程的人工潜在功能只能用于公路情景中。此外,我们可以通过增加相应地点的电荷数量,实现车辆特定部分的碰撞减缓。我们从模拟的8种不同情景中测试了192个案例的方法。模拟结果表明,拟议安全控制器的成功率比使用HJ的达标率高20 %,而在系统拆卸前,还可能降低43%的碰撞率。